2013 Special Issue: Autonomous learning in humanoid robotics through mental imagery

Authors:
Alessandro G. Di Nuovo;Davide Marocco;Santo Di Nuovo;Angelo Cangelosi
Affiliations:
Centre for Robotics and Neural Systems, School of Computing and Mathematics, Plymouth University, UK and Facoltí di Ingegneria, Architettura e Scienze Motorie, Universití degli Studi di ...;Centre for Robotics and Neural Systems, School of Computing and Mathematics, Plymouth University, UK;Dipartimento dei Processi Cognitivi, Universití degli Studi di Catania, Italy and Unití Operativa di Psicologia, IRCCS Oasi Maria SS, Troina, Italy;Centre for Robotics and Neural Systems, School of Computing and Mathematics, Plymouth University, UK
Venue:
Neural Networks
Year:
2013

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Abstract

In this paper we focus on modeling autonomous learning to improve performance of a humanoid robot through a modular artificial neural networks architecture. A model of a neural controller is presented, which allows a humanoid robot iCub to autonomously improve its sensorimotor skills. This is achieved by endowing the neural controller with a secondary neural system that, by exploiting the sensorimotor skills already acquired by the robot, is able to generate additional imaginary examples that can be used by the controller itself to improve the performance through a simulated mental training. Results and analysis presented in the paper provide evidence of the viability of the approach proposed and help to clarify the rational behind the chosen model and its implementation.